Statistics- Concept and Applications

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Title STATISTICSConcepts and Applications, Second Edition Dedication Contents List of Figures List of Tables Preface Preface to the First Edition Acronyms Notation 1 BASIC CONCEPTS OF STATISTICAL STUDIES 1.1 Population 1.2 Variable and Parameter 1.3 Sample 1.4 Basic Steps in a Statistical Study 1.5 Summary 1.6 Exercises 2 ORGANIZING A RAW DATASET 2.1 Organizing a Categorical Dataset 2.2 Organizing a Quantitative Dataset 2.3 About Outliers 2.4 Summary 2.5 Use of Technology 2.6 Exercises 3 PICTORIAL REPRESENTATION OF A DATASET 3.1 Bar Diagram or Bar Chart 3.2 Histogram 3.3 Pie Diagram 3.4 Stem-Leaf Display 3.5 Time Plot 3.6 Summary 3.7 Use of Technology 3.8 Exercises 4 SUMMARIZING A RAW DATASET 4.1 Central Tendency 4.2 Variability or Dispersion 4.3 Box-Whisker Plot (or Box Plot 4.4 Summary 4.5 Use of Technology 4.6 Exercises 5 SUMMARIZING AN ORGANIZED DATASET 5.1 Central Tendency 5.2 Variability 5.3 Summary 5.4 Use of Technology 5.5 Exercises 6 CONCEPTS OF PROBABILITY 6.1 Experiment and Sample Space 6.2 Events and Operations with Events 6.3 Probability of an Event 6.4 Basic Probability Rules 6.5 Applications of Probability Rules 6.6 Conditional Probability 6.7 Summary 6.8 Exercises 7 RANDOM VARIABLES 7.1 How Random Variables Arise 7.2 Probability Distribution of a Random Variable 7.3 Mean or Expected Value of a Random Variable 7.4 Probability Histogram of a Random Variable 7.5 Variance and Standard Deviation of a Random Variable 7.6 Summary 7.7 Exercises 8 BINOMIAL EXPERIMENTS 8.1 Structure of a Binomial Experiment 8.2 Binomial Probability Distribution 8.3 Use of Binomial Probability Table 8.4 Summary 8.5 Use of Technology 8.6 Exercises 9 NORMAL CURVE AND NORMAL DISTRIBUTION 9.1 Motivation Behind a Normal Curve 9.2 Properties of a Normal Curve 9.3 Normal Probability Distribution 9.4 Areas Under a Normal Curve 9.5 Summary 9.6 Use of Technology 9.7 Exercises 10 APPLICATIONS OF THE NORMAL DISTRIBUTION 10.1 Approximating a Binomial Probability 10.2 The Normal Theorem and the Central Limit Theorem 10.3 Summary 10.4 Use of Technology 10.5 Exercises 11 ESTIMATION OF POPULATION PARAMETERS 11.1 Parameter and Statistic 11.2 Point and Interval Estimation 11.3 Interval Estimation of Three Common Parameters 11.3.1 Interval Estimation of a Population Mean 11.3.2 Interval Estimation of a Population Standard Deviation 11.3.3 Interval Estimation of a Population Proportion 11.4 Summary 11.5 Use of Technology 11.6 Exercises 12 HYPOTHESIS TESTING FOR A SINGLE POPULATION 12.1 Concept of a Hypothesis 12.2 Tests Involving a Population Mean 12.3 Tests Involving a Population Proportion 12.4 Tests Involving a Population Standard Deviation 12.5 The Concept of P-value 12.6 Verifying Normality For A Given Dataset 12.7 Summary 12.8 Use of Technology 12.9 Exercises 13 HYPOTHESIS TESTING TO COMPARE TWO POPULATIONS 13.1 Comparison of Two Populations 13.2 Tests for Two Population Means (Independent Samples 13.2.1 Population Standard Deviations are Unknown but Equal 13.2.2 Population Standard Deviations are Unknown and Unequal 13.3 Tests for Two Population Means (Dependent Samples 13.4 Tests for Two Population Proportions (Independent Samples 13.5 Tests for Two Population Variances (Independent Samples 13.6 The P-Value Approach 13.7 Summary 13.8 Use of Technology 13.9 Exercises 14 BIVARIATE QUANTITATIVE DATA: CORRELATION AND REGRESSION 14.1 Concepts of a Bivariate Dataset 14.2 Correlation Coefficient 14.3 Inferences on a Population Correlation Coefficient 14.4 The Regression Line 14.5 Inferences on the Population Regression Line 14.6 Summary 14.7 Use of Technology 14.8 Exercises 15 BIVARIATE CATEGORICAL DATA: CONTINGENCY TABLES 15.1 Concepts of a Contingency Table 15.2 Testing Independence of Two Categorical Variables 15.3 Summary 15.4 Use of Technology 15.5 Exercises 16 MULTINOMIAL EXPERIMENTS: GOODNESS OF FIT TEST 16.1 Structure of a Multinomial Experiment 16.2 Multinomial Probability Distribution (MPD 16.3 Goodness of Fit Test of MPD for a Given Dataset 16.4 Summary 16.5 Use of Technology 16.6 Exercises 17 HYPOTHESIS TESTING TO COMPARE MULTIPLE POPULATIONS 17.1 Comparing Multiple Populations 17.2 Comparing Multiple Population Variances 17.3 Comparing Multiple Population Means 17.3.1 Data from Unrestricted (independent) Samples (One-way ANOVA 17.3.2 Data from Block Restricted Samples (Two-way ANOVA 17.4 Summary 17.5 Use of Technology 17.6 Exercises 18 QUALITY MANAGEMENT USING STATISTICS 18.1 Concept of Statistical Quality Control 18.2 Principles of Statistical Process Control 18.3 Control Charts and Hypothesis Testing 18.4 Control Charts for Quantitative Data 18.4.1 The X-chart 18.4.2 The R-chart 18.4.3 The s-chart 18.5 Control Chart for Categorical Data: p-chart 18.6 Summary 18.7 Use of Technology 18.8 Exercises Appendix A Statistical Tables Appendix B Question Bank Appendix C Multiple-Choice Questions (with Answers Appendix D Answers to Chapter Exercises Index Back cover